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Marker association study of yield attributing traits in common bean (Phaseolus vulgaris L.).

Nancy GuptaSajad Majeed ZargarRavinder SinghMuslima NazirReetika MahajanR K Salgotra
Published in: Molecular biology reports (2020)
Common bean is gaining acceptance as one of the most valuable major food consumed worldwide owing to innumerable nutritional and therapeutic benefits. Comparatively less productivity in underdeveloped countries encouraged us to proceed for QTL mining of yield traits in common bean. Heretofore, multiple yield associated markers have been detected all over the world; even so, the present work is looked on as the first report on identification of novel/new potent markers by exploiting the germplasm of Northern India. A panel of one hundred and thirty five genotypes was used for morphological studies and based on preliminary molecular evaluation; a set of ninety six diverse common bean genotypes (core set) was selected for association analysis. Molecular data generated by a total of ninety eight microsatellite markers (53 genomic and 45 genic SSRs) revealed high estimation of polymorphism among the genotypes that were observed to be divided into two major sub-populations and varying levels of admixtures based on population structure analyses. By employing both MLM and GLM analysis approaches, we identified 46 and 16 significant marker-trait associations (p ≤ 0.005) respectively, few of which have already been reported and hence validate our results. PVBR213 marker was found to be strongly associated with days to bud initiation trait when analyzed with both the approaches. Phenotypic variation of identified significant markers ranged from 3.1% to 32.7% where PVBR87, PVBR213, X96999 and X57022 explain more than 30% of phenotypic variation for 100 seed weight, days to bud initiation, pods per plant and pod length traits respectively. These findings introduce highly informative markers to aid marker-assisted selection program in common bean for high yield performance along with good agronomic merit.
Keyphrases
  • genome wide
  • body mass index
  • weight loss
  • physical activity
  • climate change
  • single cell
  • copy number
  • risk assessment
  • quality improvement
  • weight gain
  • clinical evaluation